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The need for sustainable and precise crop protection has never been more urgent [...]

Background Drought is a major limiting factor seriously influencing worldwide soybean production and its impact on yield, morphological and physiological traits depend on the timing it occurs and the intensity of water shortage. Only limited research has however been conducted on identifying the drought-tolerant genotypes at different growth stages (vegetative growth phase, reproductive growth phase and the whole growth phase) as well as evaluate the effectiveness and reliability of multiple phenotypic and yield-related characteristics in soybean. Results Two pot experiments and a 2-year field experiment were conducted to evaluate soybean drought tolerance at different growth stages. The membership function value of drought tolerance (MFVD) was used to identify drought-resistant cultivars during vegetative growth phase and reproductive growth stage; the relative drought index (RDI) of yield was used to assess drought-resistant cultivars during the whole growing period. In this study, regression models built based on MFVD indicated that the variation of drought tolerant coefficient (DC) of R/S, TRL, LAI and RSR could explain 73.70% of the total variation at vegetative growth phase. However, higher heritability only found in LAI and RSR, indicating the two traits could serve as reliable criteria for drought evaluation. Similarly, the DC of SPP, YPP, PH, PB, MSNN and STB could explain 94.30% of the total variation in MFVD according to stepwise multiple linear regression analyses at reproductive growth phase. Thus, these six traits were identified as indicators for screening drought resistance genotypes in soybean. In addition, correlation analysis revealed that the MFVD was significantly positively correlated with the DC RB , DC R/S , DC RSA , DC RSR and DC RBR at vegetative growth phase and DC YPP , DC SPP , DC RB, and DC PB at reproductive growth phase. This indicated that these traits were closely related to the drought resistance of plants. Conclusions LD24, JD36 and TF31 of vegetative growth phase, and TD37 and LD26 of reproductive growth phase were identified with drought tolerant and highly drought tolerant, respectively. Moreover, 30 accessions with drought tolerance were screened in the field trial and could be applied for the drought resistance of other genotypes by cross-breeding.

In recent years, unmanned aerial vehicles (UAVs) for plant protection have achieved rapid development in China. In order to test and evaluate the performances of pesticides application and development status of UAVs in China, four typical UAV models were selected to test the spraying coverage, penetrability, droplets density and the work efficiency. The results showed that the deposition and spraying liquid coverage were inconsistent both in lateral and longitudinal direction. Under the condition of the similar amount of spray volume and operation parameters, the volume median diameter (VMD) of the droplet was negatively correlated with the coverage density. The failure of the UAVs for plant protection mainly took up on the blockage of nozzle, transfusion tube and the liquid pump. The failure rate of UAVs took up 3.73%-4.36% of the total working time. The operation of UAVs during ground service took up 50% of the total working time, the preparation work took up 10%, and the route planning took up around 10%, while net operation time only took up around 30%. On the whole, the high efficiency of UAV was not fully achieved; the daily operated area was not in a satisfactory level now. The spraying performances of UAVs still need further improvement.

Melamine formaldehyde was used as the shell material and n-eicosane as the core material with the method of in situ polymerization to synthesize microencapsulated phase change materials (MPCMs). To enhance the thermophysical characteristics and photothermal conversion performance of the MPCM slurry, multi-wall carbon nanotubes were added, and the microscopic morphology and thermophysical parameters of the MWCNT-MPCM slurry were analyzed. The thermal conductivity, viscosity, and photothermal conversion properties of the slurry were examined. The results indicated that the synthesized MPCMs were nucleated and unbroken, with a spherical form and a latent heat of phase transition of up to 135.92 kJ/kg. The MPCM was stable when dispersed in water, and its thermal conductivity rose with the temperature but slightly decreased during the phase transition period. The viscosity rose with the addition of the MPCM, with a jump at 20% MPCM content. The addition of MWCNTs had a minor effect on the material’s thermophysical properties. The thermal conductivity increased from 0.55 W/m·°C to 0.6 W/m·°C when MWCNTs were added to the material. The viscosity of a 20% MPCM slurry exceeded 3000 mPa·s when 0.5% MWCNTs were introduced. Under 1 sun of sunlight, the mixture’s peak temperature could reach 60 °C at 0.5% MWCNT concentration. The MWCNT-MPCM slurry is capable of producing efficient solar photothermal conversion without sacrificing other thermophysical properties, and it has several applications in solar energy consumption and thermal engineering.

Soybean ( Glycine max ) productivity is significantly reduced by drought stress. Breeders are aiming to improve soybean grain yields both under well-watered (WW) and drought-stressed (DS) conditions, however, little is known about the genetic architecture of yield-related traits. Here, a panel of 188 soybean germplasm was used in a genome wide association study (GWAS) to identify single nucleotide polymorphism (SNP) markers linked to yield-related traits including pod number per plant (PN), biomass per plant (BM) and seed weight per plant (SW). The SLAF-seq genotyping was conducted on the population and three phenotype traits were examined in WW and DS conditions in four environments. Based on best linear unbiased prediction (BLUP) data and individual environmental analyses, 39 SNPs were significantly associated with three soybean traits under two conditions, which were tagged to 26 genomic regions by linkage disequilibrium (LD) analysis. Of these, six QTLs qPN-WW19.1, qPN-DS8.8, qBM-WW1, qBM-DS17.4, qSW-WW4 and qSW-DS8 were identified controlling PN, BM and SW of soybean. There were larger proportions of favorable haplotypes for locus qPN-WW19.1 and qSW-WW4 rather than qBM-WW1, qBM-DS17.4, qPN-DS8.8 and qSW-DS8 in both landraces and improved cultivars. In addition, several putative candidate genes such as Glyma.19G211300 , Glyma.17G057100 and Glyma.04G124800 , encoding E3 ubiquitin-protein ligase BAH1, WRKY transcription factor 11 and protein zinc induced facilitator-like 1, respectively, were predicted. We propose that the further exploration of these locus will facilitate accelerating breeding for high-yield soybean cultivars.

The intelligent pesticide application techniques in orchards have grown rapidly worldwide due to the decrease in agricultural populations and the increase in labor costs. However, whether and how intelligent pesticide application techniques are better than conventional pesticide application remains unclear. Here, we evaluated the performance of the unmanned aircraft vehicle (UAV) and unmanned ground vehicle (UGV) on pesticide application, ecological environment protection, and human’s health protection compared to conventional manual methods. We quantified characteristics from the aspects of working effectiveness, efficiency, environmental pollution, water saving and carbon dioxide reduction. The results showed that the UAV application has the advantages of a higher working efficiency and less environmental pollution and natural resource consumption compared to the UGV and conventional manual methods despite of its worse spray performance The UGV application techniques could improve spray performance at the cost of high environmental pollution. The conventional spray gun technique was unfriendly to environmental and resource protection although it showed a better spray performance. Thus, the balance of improving spray performance and controlling environmental pollution is the key to improve the performance of UAV and UGV technology in the future. The study could be useful in the development of intelligent pesticide application techniques and provide scientific support for the transition of intelligent management in orchards.

Dear Editor, Living cells can change their intramembranous temperature during cell activities such as division, gene expression, enzyme reaction, and metabolism [1, 2]. Moreover, under external stimuli, such as drugs or other signals, cells may quickly change their metabolic activities, leading to acute variation of intracellular temperatures from the normal state [3, 4].

The agronomic processes are complex in rice production. The mechanization efficiency is low in seeding, fertilization, and pesticide application, which is labor-intensive and time-consuming. Currently, many kinds of research focus on the single operation of UAVs on rice, but there is a paucity of comprehensive applications for the whole process of seeding, fertilization, and pesticide application. Based on the previous research synthetically, a multifunctional unmanned aerial vehicle (mUAV) was designed for rice planting management based on the intelligent operation platform, which realized three functions of seeding, fertilizer spreading, and pesticide application on the same flight platform. Computational fluid dynamics (CFD) simulations were used for machine design. Field trials were used to measure operating parameters. Finally, a comparative experimental analysis of the whole process was conducted by comparing the cultivation patterns of mUAV seeding (T1) with mechanical rice direct seeder (T2), and mechanical rice transplanter (T3). The comprehensive benefit of different rice management processes was evaluated. The results showed that the downwash wind field of the mUAV fluctuated widely from 0 to 1.5 m, with the spreading height of 2.5 m, and the pesticide application height of 3 m, which meet the operational requirements. There was no significant difference in yield between T1, T2, and T3 test areas, while the differences in operational efficiency and input labor costs were large. In the sowing stage, T1 had obvious advantages since the working efficiency was 2.2 times higher than T2, and the labor cost was reduced by 68.5%. The advantages were more obvious compared to T3, the working efficiency was 4 times higher than in T3, and the labor cost was reduced by 82.5%. During the pesticide application, T1 still had an advantage, but it was not a significant increase in advantage relative to the seeding stage, in which operating efficiency increased by 1.3 times and labor costs were reduced by 25%. However, the fertilization of T1 was not advantageous due to load and other limitations. Compared to T2 and T3, operational efficiency was reduced by 80% and labor costs increased by 14.3%. It is hoped that this research will provide new equipment for rice cultivation patterns in different environments, while improving rice mechanization, reducing labor inputs, and lowering costs.

With the aim of solving the problems of high labor intensity, low operational efficiency, and poor deposition distribution uniformity in the mango canopy associated with traditional plant protection devices, an air-ground co-operation stereoscopic plant protection system consisting of an orchard caterpillar mist sprayer and a six-rotor plant protection UAV was designed to jointly undertake plant protection operations in mango orchards. We tested the spraying performance of the system on mango trees, compared with the single-machine operation, the air–ground co-operation system could significantly increase the droplet coverage on the upperside of mango leaves in each part of the canopy (a 14.7% increase for the mist sprayer and 12.9% for the UAV). This increased the active component deposition distribution uniformity in the mango canopy but could not significantly improve the deposition and coverage of droplets on the underside of leaves compared with the mist sprayer and plant protection UAV. Due to the characteristics of the mango canopy such as large leaf length and thickness and complex leaf inclination distribution, this led to poor deposition distribution uniformity of the two spray units, and the overall CV was over 150%. The pesticide active ingredients were almost uniformly distributed in the vertical direction when the application ratios (ground implements/plant protection drones) were 8/2 and 7/3, offering a promising protocol for reduced pesticide application in mango orchards. This study presents promising data that support the innovative integration of drones into crop protection programs for large canopy crops (e.g., mango) and provides guidance for the ACSPPS system in reduction and precision application research.

Background: Unmanned Aerial Vehicles (UAVs) are increasingly being used commercially for crop protection in East Asia as a new type of equipment for pesticide applications, which is receiving more and more attention worldwide. A new model of pear cultivation called the ‘Double Primary Branches Along the Row Flat Type’ standard trellised pear orchards (FT orchard) is widely used in China, Japan, Korea, and other Asian countries because it saves manpower and is suitable for mechanization compared to traditional spindle and open-center cultivation. The disease and pest efficacy of the flat-type trellised canopy structure of this cultivation is a great challenge. Therefore, a UAV spraying trial was conducted in an FT orchard, and a four-factor (SV: Spray application volume rate, FS: Flight speed, FH: Flight height, FD: Flight direction) and 3-level orthogonal test were designed. Results: These data were used to analyze the effect, including spray coverage, deposit density, coefficient of variation, and penetration coefficient on the canopy, to determine the optimal operating parameters of the UAV for pest efficacy in FT orchards. The analysis of extremes of variance showed that factor FD had a significant effect on both spray coverage and deposition density. Followed by factor FS, which had a greater effect on spray coverage (p < 0.05), and factor SV, FH, which had a greater effect on deposition density (p < 0.05). The effects of different factors on spray coverage and deposit density were FD > FS > FH > SV, FD > FH > SV > FS, in that order. The SV3-FS1-FH1-FD3, which flight along the row with an application rate of 90 L/ha, a flight speed of 1.5 m/s, and a flight height of 4.5 m, was the optimal combination, which produced the highest deposit density and spray coverage. It was determined through univariate analysis of all experimental groups, using droplet density of 25/cm2 and spray coverage of 1%, and uniformity of 40% as the measurement index, that T4 and T8 performed the best and could meet the control requirements in different horizontal and vertical directions of the pear canopy. The parameters were as follows: flight along the tree rows, application rate not less than 75 L/ha, flight speed no more than 2 m/s, and flight height not higher than 5 m. Conclusion: This article provides ample data to promote innovation in the use of UAVs for crop protection programs in pergola/vertical trellis system orchards such as FT orchards. At the same time, this project provided a comprehensive analysis of canopy deposition methods and associated recommendations for UAV development and applications.